Postdoc @uusci | Previously, postdoc @UniofOxford | PhD @UniversityLeeds | #CompBiochem #Tech #SciArt ➡️ https://xitter.cf/t.co/uqiLhhxsbg
Salt Lake City, UT, USA
Joined February 2018
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Dheeraj Prakaash retweeted
🚨 NVIDIA × Nobel laureate David Baker’s team just unveiled RFD4-Proteina.
Protein design is entering the reasoning era.
The model unifies proteins, noncanonical amino acids, sugars, DNA, and RNA in a shared latent space, enabling iterative refinement and inference-time search.
🧬 10.6% computational success rate on protein binder design benchmarks, with 42× the throughput of BindCraft.
Even more impressive: wet-lab validation includes a de novo designed enzyme for a key step in the synthesis of the HIV drug lenacapavir.
Code and model weights are now available.
🔗 rfd4-proteina.org/
Dheeraj Prakaash retweeted
🧬 Design proteins faster and send fewer, better candidates to the lab.
Introducing RFD4-Proteina, a new NVIDIA BioNeMo open model co-developed with @UWproteindesign.
▫️Fast: 13× faster generation than RFdiffusion3 at 200 residues
▫️ Smart: state-of-the-art across 12+ protein design tasks
▫️ Programmable: set your design inputs and use test-time compute on harder problems
Start with our binder-design tutorial nvda.ws/3VK9Uvr
Dheeraj Prakaash retweeted
🧬 Design proteins with natural language.
Pinal is now online in Nature!
Pinal democratizes computational protein design by turning functional intent into protein candidates.
Open weights + code: github.com/westlake-repl/Den…
Paper: nature.com/articles/s41586-0…
Dheeraj Prakaash retweeted
Public preview of BioEmu2! @MSFTResearch AI for Science’s new foundation model for biomolecular structure, dynamics and function. Open weights, MIT license.
github.com/microsoft/bioemu2
Movie: BioEmu2-simulated binding of intrinsically disordered peptide PUMA to MCL-1 receptor. 🧵⬇️
Dheeraj Prakaash retweeted
David Baker’s team just unveiled Chaperone, an AI agent harness for protein design.
🧬 86% fewer tokens
⚡ 64% fewer GPU-hours
📈 Computational pass rate nearly doubled (6.1% → 11.7%)
Plus, a 1.32 nM cortisol binder designed in just 2 weeks.
🔗 github.com/RosettaCommons/ch…
🤖 Made with AI
Dheeraj Prakaash retweeted
We are bringing agents to the wet-lab bench at Google Research to navigate complex biological landscapes. Learn how we are grounding agents in physical lab robotics to run fast closed-loop molecular design cycles, ultimately discovering single-digit nanomolar protein binders for cancer targets →goo.gle/4B5mMMB
Dheeraj Prakaash retweeted
Today, RFdiffusion3 is out in @ScienceMagazine!
science.org/doi/10.1126/scie…
We have many exciting updates to share! We're also releasing Chaperone, an agent harness for general bio-molecular design. 1/n
Dheeraj Prakaash retweeted
Our AM-3 paper is out in Cell. Opioids are critical drugs, but have severe side effects. Because they are administered systemically, it is hard to dissect how they work, and to separate side effects. So we built one you can switch on and off with light. cell.com/cell/abstract/S0092…
Dheeraj Prakaash retweeted
🚨 OpenAI is bringing GPT-Rosalind to academic labs!
The new **Rosalind Academic Plan** offers eligible U.S. university labs:
🧬 Access to OpenAI's specialized life sciences model
🔬 Up to 30 free seats for 12 months
🧪 AI tools for protein design, genomics & drug discovery
Access is subject to approval.
openai.com/index/introducing…
🤖 Made with AI
Dheeraj Prakaash retweeted
also works with *molecular* machines!
here, ATP Synthase, a 25nm rotary motor in your cells that uses a flow of protons to make ATP, the molecule that powers almost everything a cell does
Introducing Anatomy
Describe a machine in one line. Claude brings it to life.
- Interactive isometric wireframes you can rotate, inspect and explore
- WebGL shaders for fire, water, plasma and more
- Real 3D motion, with individual parts that rotate and move
Install it as an agent skill. Fully open source.
Dheeraj Prakaash retweeted
Introducing AlphaProtein Novo, a pipeline for de novo enzyme design! In collaboration with @francesarnold's group, we developed AP Novo and used it to get SoTA "novel-scaffold" activity on 2 benchmark reactions and create enzymes to synthesize the pharmaceutical motif piperidine and degrade the environmental toxin DEHP.
Work led by @ZvxyWu @ZiqiLi0513 with teammates @alexechu_ @kelly_ruijie @schulluc @jacobjinkelly @rosaliags @davidla @solserpens @j_reisenbauer, @pengliu_group, Josh, Thomas, Amy, Tristan, Harshnira, and others. It was a joy and privilege to work with you all!
Preprints and code:
biorxiv.org/content/10.64898…
biorxiv.org/content/10.64898…
github.com/google-deepmind/a…
Dheeraj Prakaash retweeted
Today we are announcing Topos-2, our next-generation model for generating the full range of shapes a protein can take, across the order-disorder spectrum.
We are also previewing Topos-Bind: to our knowledge, the first generative model to capture the range of shapes for disordered proteins bound to small molecules.
Read the technical blog post here: toposbio.ai/topos-2-topos-bi…
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Dheeraj Prakaash retweeted
The 2026 Nobel Prizes are awarded next week! We crunched the data on the winners in scientific fields to see who is most likely to win
Accurate based on data 1901-2023
go.nature.com/3TmdcUK
Dheeraj Prakaash retweeted
Now Gemini can connect with 13 new apps like @adobe, @squarespace, @onepeloton, and more.
Instead of switching between tabs, you can now grow your business, design assets, and plan your workouts all in Gemini. 🧵
Dheeraj Prakaash retweeted
Cell just dropped a full Focus Issue on AI in Biology.
Virtual cells. World models. 500M+ cell repositories. 100M-scale perturbation atlases. Aging benchmarks. 4D mitochondria. Multimodal cancer prediction.
Here are the 13 pieces worth reading 🧵
🤖 Made with AI
Dheeraj Prakaash retweeted
Interested in molecular animation? Give ProteinBlender a try! It's free and open source. animation-lab.github.io/Prot… The latest tools include a DNA builder (shown in the tutorial video below). We'd love to hear what you think! We have short tutorials that cover all the features!
Dheeraj Prakaash retweeted
👋 Say hello to faster structure prediction
NVIDIA BioNeMo Inference Runtime is in public beta. This open, PyTorch-native library speeds up biomolecular inference on NVIDIA GPUs.
Optimize models including Boltz-2, OpenFold2, and Protenix v2 with specialized kernels and, where supported, CUDA Graphs - then scale with Ray-powered GPU replicas.
🙌 Huge thanks to our collaborators at @apheris_AI, @AurekaBio, @Biomap_IMI, @boltz_bio, @dataiku, @UWproteindesign, @Latent_Labs, MoleculeMind, @nebiusai, @openmsf, @open_fold, @proximabio, @SandboxAQ, @Terray_Tx, and @Xaira_Thera for partnering with us on this work.
📃 nvda.ws/46PDmlL
